mport the iris data using: [WITH PYTHON]

import numpy as np import matplotlib.pyplot as plt import seaborn as sns import pandas as pd

from sklearn.neighbors import KNeighborsClassifier from sklearn.metrics import accuracy_score from sklearn.cross_validation import train_test_split from sklearn import datasets

iris = datasets.load_iris() X = pd.DataFrame(iris['data'], columns = iris['feature_names']) Y=iris['target']

Task:

Problem 4: Apply a k-Nearest Neighbors classifier (30 points) Train a three-class k-NN classifier (sklearn.neighbors.KNeighborsClassifierD on the Iris data with 9 neigh- bors. Report the numerical error rate. Visualize the separation plane in 2-dimensional PCA space. (Hint: The point on the hyperplane has similar probability estimates to two classes.)